In critical areas such as the design of human implantable devices (chips) (Figure 3), the reliability of implanted systems is clearly critical. Forbes Insight, Jersey City (2017) Haller, S., Karnouskos, S., Schroth, C.: The Internet of Things in the Enterprise Context.
A New Reconfigurable Architecture with Applications to IoT and Mobile
Computing
1 Introduction
In the traditional FPGA devices, the routing network, due to its complexity, occupies a large part of the chip area; consequently the power consumption increases. Starting from a data flow graph model of the application, ILP formulation leads to efficient mapping of the application to our proposed architecture, as well as the optimum latency for the execution of the application. Additionally, we introduced heuristics to improve the efficiency of the routing method for larger circuits.
Our proposed mapping method for large scale routine computations is based on automatic mapping for small problem instances and induction generalization for larger problem. Note that due to our simpler and more regular routing architecture compared to traditional FPGA devices, very deep pipelining can be achieved at a higher clock frequency, which in turn improves the computational performance on our proposed architecture.
2 Background
Reconfigurable Hardware
Integer linear programming (ILP) is an optimization method that attempts to find values for a set of integer variables given a set of linear constraints, such that a linear function is minimized or maximized. There are numerous problems in the field of electronic design automation (EDA) that can be compared to an ILP problem, including scheduling and routing, which is the objective of this paper.
3 Hardware Architecture
Therefore, to transfer data from a CLB to other non-neighboring CLBs, some CLBs between them must be used as transfer points. However, in an FGPA, data can be transferred from any CLB to any other CLB as long as there is an available routing resource. Consequently, data transfers in FPGA can take a long time, increasing the critical path delay and decreasing the clock frequency.
However, in our proposed architecture, all data transfers are between two neighboring CLBs, and take exactly one clock cycle. Another important feature of our proposed architecture is that the critical path delays are fixed; so the timing closure problem cannot occur.
4 General Mapping Method
ILP Variables
This means that a given application, when mapped to our architecture, can result in a very deep pipeline. In general, having a very deep pipeline helps improve performance, although latency may increase. D(op, t, p): op data is mapped to be used at cycle CLB numberp op,t and p parameters are shown in Fig.6.
Assuming that each gate in the image will run on a single LUT, one possible way is as follows.
ILP Constraints
A New Reconfigurable Architecture 139 Note that in the definition of variables we have assumed that any operation can be mapped to any CLB, which means that all CLBs are capable of performing any DFG node function. However, in general, we can have different DFG node types and different CLB types, and each type of DFG node can be mapped to different CLB types. Furthermore, due to the proposed architecture, data transmission constraints make sure that the correct sequence of data transmission is performed, which means that data is transmitted to the neighboring nodes in only one cycle.
In our problem, the goal is to map in such a way that the delay is minimal, which means that the last cycle in which any node of DFG (T) is executed is minimal. Otherwise, the problem has no solution, which means that the execution of a given DFG in a given architecture cannot be completed in less than T cycles.
5 Regular Computations Mapping Method
Matrix-Vector Multiplication
Figure 8 shows the multiplication of a 4×4 matrix, and Figure 9 shows its corresponding data flow graph mapped to 4 blocks. The data flow between the blocks is like a ring connection, and the mapping follows the "natural" sequence of operations by a human. As shown in the figure, the mapping in this case is not optimal, as it requires a lot of global data transfers between the blocks.
In the first solution, the partial products are propagated from one block to its neighboring block, while in the second solution, the input vectors are propagated. The above observations about the flow of data in the solution can be made by a human, and this knowledge can be used in a program to automatically generate and verify the solution for larger size matrices, as shown in the experimental results section .
Convolutional Neural Networks
Following the proposed method, we have tried to find the optimal solution for this matrix-vector multiplication.
6 Experimental Results
As the results show, the complexity of finding an optimal solution increases by increasing the number of DFG nodes and the number of I/O of the circuit. In the following experiment, we tried to improve the ILP resolution time by dividing the DFG into 2 sections so that each section is implemented in one of the 2 partitions of the hardware, as shown in Fig.15. In addition, for one of the cases that could not be solved due to timeout, the optimal solution is obtained.
However, for one of the circuits we still cannot find the optimal solution and we need other heuristics to further reduce the execution time, and this is part of our future work. Without the generalization of the solution to 4×4 matrices, the problem for matrices larger than 8×8 could not be completed in a day.
7 Conclusions
Sensors can be classified based on the specific physical or chemical properties they measure (eg air pressure, temperature, acceleration), or - in the case of fusion sensors that combine the results of multiple underlying sensors - the calculated result that they give (eg the absolute orientation of a device). Evans, D.: The Internet of Things - how the next evolution of the Internet is changing everything. The emergence of the Internet of Things (IoT) has brought improvements and new development opportunities to the automotive industry, such as electric vehicles (EV).
Another limitation was that a full evaluation of the data integration platform needed to be completed. There are a number of design flaws, but I wouldn't say the stress aspect is a flaw in the system, instead it has… it's the human factor. Case studies of the use of IoT in the WASH sector in developing countries and, where possible, in Africa provided additional background.
Santucci, G.: The internet of things: between the revolution of the internet and the metamorphosis of objects (2011).
IoTutor: How Cognitive Computing Can Be Applied to Internet of Things
Education
Therefore, adequate training of the future workforce is a prerequisite for success in the increasingly relevant IoT domain. Predicting the likely answer involves determining the main features of the question by generating hypotheses and evaluating possible answers taking into account the context and iterative learning from each instance of interaction with the cognitive system. In this paper, we propose to use cognitive computing for training students in the IoT domain.
We deployed the IoTutor as a cross-platform web-based application using a collection of the IBM Watson cloud services, including the Discovery service, text-to-speech, and speech-to-text services. Through a user experience survey, participants were asked to rate the attractiveness, acumen, efficiency, stimulation, and novelty of the IoTutor.
2 Related Work
3 Design and Implementation
Design
If the user wants to use voice commands, then the microphone button needs to be pressed, which will create a back-end transmission between IoTutor and Watson's speech-to-text, and familiar words will appear in the question box. If the user does not toggle the microphone from on to off, IoTutor will still recognize voice commands and display the text in the question box. These details include a link to the full article and an option to allow IoTutor to read the full text to the user.
Clicking on the full article link will take the user to the full pdf file. When the close button is clicked, the modal window closes and the user can choose to expand on another answer or ask a new question.
Implementation Details
The discovery component is a simple application programming interface (API) that takes requests (in this case, questions) from the front end and sends them to the Watson Cloud Discovery service. When a response is received from the Watson Discovery service, the back-end forwards the response to the front-end. In addition, the backend has a database of files that have been imported into Watson Discovery and can easily map the response to an actual scientific publication, so if the user wants to read more, the backend can provide a link to the paper.
Basically, it can set up a stream that can listen to the user's microphone and display the recognized text in the IoTutor GUI input field, and can create an audio file corresponding to the given text input. Similar to the discovery component, it first authenticates to the text-to-speech or speech-to-text service using the information provided by the env.json file, and then can send specific requests to the Watson Cloud text-to-speech or speech-to-text service.
4 Evaluation
Demonstration
To implement our application, we used HTML5, CSS and JS in the front-end, while NodeJS [2] is used in the back-end. Among other things, in the backend we used the Watson Node SDK [3] to access the IBM Watson Developer Cloud services. For the voice commands to work on the front end, which requires data to be encrypted, we enabled the Hyper Text Transfer Protocol Secure (HTTPS) on our server (Table 1).
View of the chat area, including the greeting message, questions, answer list, question box, and microphone toggle button. Expanded response view, including article information (title, authors, year), text-to-speech functionality, and expanded response.
Evaluation Method and Results
Most of the participants were students taking an Internet of Things master's level course at Linnaeus University. IoTutor 229 The results of the UEQ show a trend that participants expressed an overall positive attitude towards the tool. When looking cumulatively at each of the five aspects/dimensions, all ratings appear above the neutral value (see Fig.7).
Since the clarity and efficiency aspects measure the usability of the tool, and the simulation and novelty aspects measure the user experience, the indication is that both show similar ratings. 6. The mean and standard deviation for each of the answers in the user experience questionnaire.
5 Conclusions and Future Work
Participants expressed their opinion on the attractiveness, transparency, efficiency, stimulation and novelty of IoTutor. In: Proceedings of the Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), p. Chozas, A.C., Memeti, S., Pllana, S.: Using Cognitive Computing to Learn Parallel Programming: The IBM Watson Solution.
High, R.: The age of cognitive systems: A look at IBM Watson and how it works. Mercer, C.: 16 Innovative Businesses Using IBM Watson: Which Companies Are Using Watson's Big Data and Analytics to Power Their Business.
